A Corpus-Based Learning Method of Compound Noun Indexing Rules for Korean

In Korean information retrieval, compound nouns play an important role in improving precision in search experiments. There are two major approaches to compound noun indexing in Korean: statistical and linguistic. Each method, however, has its own shortcomings, such as limitations when indexing diverse types of compound nouns, over-generation of compound nouns, and data sparseness in training. In this paper, we propose a corpus-based learning method, which can index diverse types of compound nouns using rules automatically extracted from a large corpus. The automatic learning method is more portable and requires less human effort, although it exhibits a performance level similar to the manual-linguistic approach. We also present a new filtering method to solve the problems of compound noun over-generation and data sparseness.     

Inclusive Education in China: Conceptualisation and Realisation

This paper examines the historical background of the development of special education and how “Learning in Regular Classrooms” (LRC) has become the major service delivery model to universalise compulsory education for children with disabilities in China. The authors assert that the current model of inclusive education in China was conceptualised through the influence of the Western ideology of inclusion and the practical consideration of Chinese socio-economical conditions. To realise this model, a number of strategies were introduced and widely practised in an attempt to effectively implement the LRC programs. Adverse social climate, the exam-oriented education system, and limited resources in all aspects, however, remained as critical elements to be overcome for the future development of inclusive education in China. The LRC model is expected to continue to be the main form of inclusive education in China.     

Educational and Employment Testing: Changing Concepts in Measurement and Policy

How will the expansion of the concept of construct validity affect validation practice in employment testing? How does the need for consequential validity differ in educational and employment testing? How do the research bases differ for performance assessment in these settings? Are there parallel trends in policies for test use in education and industry?     

Normative behavior and information: The social aspects of information access

Information access is central to library and information science, yet explorations of its conceptual nature have been limited. Given the importance of information access to the discipline, there is a need for research to create a better understanding of the concept and its many roles in all activities and behaviors related to information. Drawing on the theoretical work of Elfreda Chatman, this article proposes that the study of information access can be facilitated through the recognition and examination of the physical, intellectual, and social aspects of information access. These types of access are examined through three case studies in terms of different information behaviors and contexts, with a particular focus on the importance of social access. The article also discusses the future roles that considerations of social access can play in research and theory.     

A Little Fire in BurgerLand

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Construction of query concepts based on feature clustering of documents

In Information Retrieval, since it is hard to identify users’ information needs, many approaches have been tried to solve this problem by expanding initial queries and reweighting the terms in the expanded queries using users’ relevance judgments. Although relevance feedback is most effective when relevance information about retrieved documents is provided by users, it is not always available. Another solution is to use correlated terms for query expansion. The main problem with this approach is how to construct the term-term correlations that can be used effectively to improve retrieval performance. In this study, we try to construct query concepts that denote users’ information needs from a document space, rather than to reformulate initial queries using the term correlations and/or users’ relevance feedback. To form query concepts, we extract features from each document, and then cluster the features into primitive concepts that are then used to form query concepts. Experiments are performed on the Associated Press (AP) dataset taken from the TREC collection. The experimental evaluation shows that our proposed framework called QCM (Query Concept Method) outperforms baseline probabilistic retrieval model on TREC retrieval.